The present study is proposed to study the effectiveness of IT based farm advisory service and its extent of replication and scalability to meet the long standing gap with the following objectives. Hence, the research was taken with an objective to develop and standardize a scale to measure the perception and acceptance of farmers about information technology (IT) enabled Comprehensive Farm Advisory Services by the Farmers.
Trang 1Original Research Article https://doi.org/10.20546/ijcmas.2020.907.385
Development of a Scale to Measure the Perception and Acceptance of Information Technology (IT) Enabled Comprehensive Farm Advisory
Services by Farmers
N Rajeshwari* and S S Dolli
Department of Agricultural Extension Education, College of Agriculture, Dharwad,
University of Agricultural Sciences, Dharwad, India
*Corresponding author
A B S T R A C T
Introduction
Agriculture continues to be the most
important sector of Indian economy research,
extension and farmers efforts have all
contributed significantly to increase in food
production The total demand for food grains
is projected to touch 280 million tonnes by
the year 2020-21 Meeting this demand will
necessitate a growth rate of nearly 2 per cent
per annum in food grain production and agriculture sector need to grow targeted 4 per cent per annum However the extent of adoption is found to be very low (18- 19 %) One of the reasons for wide gap is extension worker to farmer ratio resulting in low access
to technical information The gap is still widening this may be because of faulty delivery of extension system Some of studies
of ICT have demonstrated their effectiveness
ISSN: 2319-7706 Volume 9 Number 7 (2020)
Journal homepage: http://www.ijcmas.com
A scale was developed to measure the “Perception and Acceptance of Information Technology (IT) Enabled Comprehensive Farm Advisory Services by Farmers” The Likert‟s summated rating scale was followed in the construction of scale Based on the review of literature and discussion with the expert‟s, 66 statements were enlisted The relevancy rating were sent to 250 scientists and extension specialists working in research institutes of Indian Council of Agriculture Research (ICAR), State Agricultural University and development departments for critical evaluation of statements on a 5 point continuum Out of 250 judges 100 judges responded in time Based on their judgment an aggregate of
53 statements were selected by finding the relevancy weightage scores (RWS) Statements having an equal or more RWS of 0.75 and mean relevancy score of 3.00 were selected for the item analysis In item analysis the selected statements were administered to 40 farmers
in non-sample area of Navalgund taluk in Dharwad district of Karnataka state during 2018-2019 Finally a total of 48 statements were selected for the study based on „t‟ values (> 1.75) resulted from the item analysis and were included in the final scale The „r‟ value
of the scale was found to be 0.9, which was significant at one per cent level indicating the high reliability Hence, the scale developed was found to be reliable and valid The instrument developed to measure the perception and acceptance of information technology (IT) enabled farm advisory services can be used by the researchers
K e y w o r d s
Perception,
Acceptance, IT
enabled farm
advisory services,
Item analysis,
Reliability and
Validity
Accepted:
22 June 2020
Available Online:
10 July 2020
Article Info
Trang 2in filling the information gap and increased
adoption of improved technology Gandhi et
al., (2008) indicated that the Digital Green
project increased the adoption of certain
agriculture practices seven-fold over a classic
extension approaches Further, 85 per cent of
adoption of improved technologies achieved
as against 11 per cent of adoption by
traditional extension methods Similarly
Krishnareddy and Ankaiah, (2005) reported
that deploying e-Sagu prototype increased
income of the farmers for the tune of INR
3075 (63 USD) per ha and also reduced the
pesticide usage Saravanan (2008) reported
the cost and time indicators comparing
traditional extension system and e-Arik
(e-agriculture) project sixteen fold and three fold
less time were required to the clientele
availing, extension system delivering
extension services, respectively He further
reported that 3.4 fold economic benefit as
compared to the expenditure of deploying
e-agriculture prototype Hence, Comprehensive
Agribusiness Extension Services (CABES) an
IT enabled farm advisory service initiated by
UAS, Dharwad in collaboration with Indian
Institute of Business Management, Bangalore
and Scope NGO is one of the attempts to
demonstrate the education on improved
technology to farmers Here an attempt is
made to provide comprehensive information
on farm management on real time basis to
improve adoption, productivity and
profitability Hence, in order to study the
effectiveness of IT based farm advisory
service and its extent of replication and
scalability to meet the long standing gap a
scale was developed to know the perception
and acceptance of information technology
(IT) enabled comprehensive farm advisory
services by farmers According to Udai
“Pareek perception is defined as the process
of receiving, selecting, organizing,
interpreting, checking and reacting to sensory
stimuli and data” in the present context the
perception on IT based farm advisory
services– It is the organization, understanding and interpretation of information technology (IT) enabled Comprehensive Farm Advisory Services by the Farmers Hence, the present study is proposed to study the effectiveness of
IT based farm advisory service and its extent
of replication and scalability to meet the long standing gap with the following objectives Hence, the research was taken with an objective to develop and standardize a scale to measure the perception and acceptance of farmers about information technology (IT) enabled Comprehensive Farm Advisory Services by the Farmers
Materials and Methods
The present study was carried out during 2018- 2019 Forty farmers from a non-sample area were personally interviewed The method suggested by the Likert (1932) in developing summated rating scale was used to construct the perception scale The details of the procedure followed and standardization of the scale to measure the perception of farmers about information technology (IT) enabled Comprehensive Farm Advisory Services
Collection of items / statements
About 90 draft statements on the perception and acceptance of farmers about Information Technology enabled farm advisory services were collected based on review of literature, journals, thesis discussion with relevant specialists and researcher‟s own experience These statements were carefully edited in the light of 14 criteria suggested by Edword (1969) Thus, 66 statements (Appendix I) were selected for further analysis
Relevancy weightage test
All the statements collected may not be relevant equally in measuring the perception and acceptance of farmers about Information
Trang 3Technology enabled farm advisory services
Hence, these statements were subjected to
scrutiny by an expert panel to determine the
relevancy and screening for inclusion in the
final scale For this, the list of scrutinized 66
statements were sent to a panel of 150 experts
with request to critically evaluate each
statement for its relevancy to measure
perception of farmers about Information
Technology enabled farm advisory services
The experts comprised scientists of ICAR
Research Stations and Institutions, Subject
matter specialists in KVKs, Agricultural
Extension scientists from State Agricultural
Universities, Agricultural Scientists from
Directorate of Extension who had knowledge
in Information Communication Technology
and were involved in field level extension for
critical evaluation
The experts were requested to give their
response on a fivepoint continuum viz., Most
Relevant, Relevant, Somewhat Relevant, Less
Relevant and Not Relevant with scores 5,4,3,2
and 1 respectively for positive statementsand
Most Relevant (MR), Relevant (R),
Somewhat Relevant(SWR) Less Relevant
(LR) and Not Relevant (NR) for
appropriateness of each statement with the
score of 1,2,3,4 and 5 for negative statements
respectively
Out of 150 experts only 50 responded in a
time span of two months The relevancy score
of each item was ascertained by adding the
scores on rating scale for all the 50 experts‟
responses From the data gathered Relevancy
Percentage (RP), Relevancy Weightage (RW)
and Mean Relevancy score (MRS) were
worked out for all the 66 items/ statements by
using the following formulae
MR 5 + R 4+ SWR 3 + LR x 2 + NR 1 Relevancy Percentage (RP) = - 100
Maximum possible score (66 X 5 =330)
MR 5 + R 4+ SWR 3 + LR x 2 + NR 1 Relevancy Weightage (RW) = -
Maximum possible score (66 5 =330)
MR 5 + R 4+ SWR 3 + LR x NR 1 Mean Relevancy Score (MRS) = -
Number of judges respondent
Using these three criteria the statements were screened for their relevancy Accordingly, statements having relevancy percentage more than relevancy weightage more than 0.75 and mean relevancy score more than 3.00 were considered for final selection of statements
By this process, out of 66 statements, 53 statements have relevancy percentage >75, relevancy weightage >0.75 and mean relevancy score >3.00 and were isolated in the first stage of screening, suitably modified and rewritten as per the comments of experts Thus finally 53 statements (Table 2) were selected after the relevancy test
Item analysis
The selected 53 statements were subjected to item analysis to demarcate the items based on the extent to which they can differentiate the respondents with high perception and low perception ICT enabled farm advisory services Thus scrutinized statements representing the perception of farmers about
IT enabled farm advisory services were administered to 40 respondents from non sample area of Navalgund taluk of Dharwad district of Karnataka state during 2018-2019 The respondents were asked to indicate their degree of agreement or disagreement with
each statement on a five point continuum viz.,
strongly agree, agree, undecided, disagree and strongly disagree with scores of 5, 4, 3, 2 and
1, respectively and negative statements scores were reversed
The respondents‟ responses were recorded and the summated score for the total
Trang 4statements of each respondent is obtained For
each respondent the maximum possible score
for 53 statements was 265 and the minimum
was 53 The scores of the respondents were
then arranged in a descending order The 25
per cent from highest scores (high group) and
25 per cent from lowest scores (low group)
were taken for the item analysis These
responses were subjected to item analysis for
selection of the items that constitute the final
perception and acceptance scale
The critical ratio i.e., t-value which was a
measure of the extent to which a given
statement differentiates between the high and
low groups of respondents for each statement
was calculated by using the following formula
Where,
= The mean score on given statement of
the high group
= The mean score on given statement of
the low group
∑X2
H = Sum of squares of the individual
score on a given statement for high group
∑X2
L = Sum of squares of the individual
score on a given statement for low group
n = Number of respondents in each group
t= The extent to which a given statement
differentiate between the high and low
group
After calculating the t- values for all the items
of the attitude scale using the formula, the
values of the statements were arranged in
descending order from the highest to the lowest and 48 statements were selected from the scale whose values are highest i.e., with t- values more than 1.75, for both positive and negative statements
Selection of Perception and Acceptance Statements for final Scale
After computing “t” value for all the items, 48 statements with highest “t” value equal to or greater than 1.75 were selected The thumb rule of rejecting items with „t‟ value less than 1.75 was followed Edwards A L (1957)
As per the thumb rule selection of items to be retained in the scale, includes the scales with highest discriminating values excluding the scales with poor discriminating ability and questionable validity Thus, 48 statements were retained for consideration in the final scale based on the following norms:
The „t‟ value should be more than 1.75 The statement should present a new idea i.e., the idea not overlapping with that expressed other
The statement should be simply worded and brief
Reliability and validity of Perception and Acceptance Scale
The scale developed was further standardized
by establishing its reliability and validity
“Reliability is the accuracy or precision of measuring instrument” by Ganeshkumar and Ratnakar (2011) To know the reliability of the attitude scale Split-Half method was followed As validity literally means truthfulness, which refers to “the degree to which a test measures, what it claims to measure” by Kerlinger (1973), content validity was used to measure the validity of the scale
Trang 5Split-Half methodology
The reliability of the scale was determined by
„Split-Half‟ method The split-half method
was regarded by many as the best of the
methods for measuring reliability
The 24 selected attitude items were divided
into two halves by odd-even method The two
halves were administered separately to 20
farmers in a non-sample area
The scores were subjected to product moment
correlation test in order to find out the
reliability of the half-test The half-test
reliability coefficient (r) was 0.90, which was
significant at one per cent level of probability
Further, the reliability coefficient of the whole
test was computed using the Spearman-Brown
prophecy formula given below
r 1/2 = n(∑XY–(∑X) (∑Y)
(n∑X 2 – (∑ X) 2 ) (n∑ Y 2 – (∑ Y) 2
Where,
∑X =Sum of the scores of the odd number
items
∑Y =Sum of the scores of the even
numbers items
∑X2
= Sum of the squares of the odd
number items
∑Y2
= Sum of the squares of the even
number items
n = Number of respondents
The whole test of the scale was 0.99, which
was highly significant at one per cent level
indicating the high reliability of the scale
Content validity of the attitude scale
The validity of the scale was established through content validity i.e., the representativeness or sampling adequacy of the content of a measuring instrument The scale satisfies both these criteria as the clause
of universe of statements that could be made about ICT enabled farm advisory services is formulated from the standards and also in consultation with experts who had knowledge about the psychological object This ensures high content validity of perception and acceptance scale The scale was constructed
in accordance with the steps followed in summated rating scale given by Edward A L (1957) Therefore, it was assumed that the scores obtained by administering this scale measured nothing other than the perception and acceptance of ICT enabled farm advisory services While selecting perception statements, due care is taken for obtaining a fair degree of content validity The calculated
“t” value being significant for all the finalized statements of the score indicated that the perception statements of the scale have discriminating values Hence, it seems reasonable to accept the scale as a valid
measure of the perception
Administration and scoring of perception scale
The final scale consisted of 48 statements (Table 3) The responses had to be recorded
on a five point continuum representing strongly agree, agree, undecided, disagree and strongly disagree with scores of 5, 4, 3, 2, and
1, respectively for positive statements and vice versa for negative statements The perception score on this scale ranges from a minimum of 48 to maximum of 240 Higher the perception score indicates the more good perception of farmers about ICT enabled farm advisory services and lesser perception score indicates bad perception of farmers about ICT enabled farm advisory services
Trang 6Table.1 Scale on perception and acceptance of information technology (IT) enabled
comprehensive farm advisory services by farmers Relevancy Percentage, Relevancy Weightage, Mean Relevancy Scores and „t‟ values
1 Comprehensiveness of content
1 The content given through the TAB in
digital form includes all production
practices
3 I can get information on any problem I
request in digital form
4 The content /message includes more on
pest management than other topics
5 The content updated includes latest
technology of crops
6 The information received through digital
media is incomplete
2 Field Applicability
7 Information provided through TAB has
complete field applicability
8 Some of the recommendations cannot be
applied in the field
9 I can use the advices in the TAB as per
my field conditions
10 Inputs suggested in the TAB are not
available in market
11 The best management practices given in
the TAB are applicable to my field
12 Holistic solutions provided by TAB is
suited to all types of formats
3 Solution for undiagnosed pests
13 The application in the TAB makes the
pest and disease identification and
diagnosis easier
14 It provides latest and updated information
in pest management
15 When new pest or disease is observed it is
difficult to get timely solution through the
TAB
16 Proper identification of pests, pesticides,
chemicals help to reduce injudicious use
of pesticides by farmers
17 Solutions for undiagnosed pests are
received within 24 hours
Trang 718 Pest identification is easier with the help
of digital device
4 Timeliness
19 The advice is available at right time on
real time bases
20 TAB enabled advice is not available
when requested
21 Solution provided for pest and disease
identification were timely
22 The timeliness of the information helped
to reduce crop losses
23 Using TAB we can get any information at
any time
24 We have to wait for the field staff to get
information from TAB
25 The information includes
recommendations by University and
ICAR
26 The information provided contradicts
with the information provided by other
sources like seed companies and private
agencies
27 The recommendations are not specific to
my crop/area
28 The information provided by TAB is
precise and real
29 The TAB provides information on all
stages of crop growth
30 All the proportions of inputs and other
recommendations mentioned in the digital
device are correct
31 The information is delivered on the spot
in the printed form
32 The interactive time between the scientist
and the farmer is short
33 Farmer has to wait for the field staff to
get the information
35 The device is not suitable for rural areas
due to connectivity issues
36 Time is saved as the recommendations
are received then and there
7 Presentation of Audio Visual Content
Trang 837 The pictures and videos in the TAB gives
a contrived experience
38 The visual images help in identifying the
symptoms of insect pest and diseases
39 Farmer himself can handle the device as it
is guided by pictorial images
40 The pictures are not clear and confusing 70.40 00.70 3.26 2.60
41 Audio Visual pictures only on some
practices gives clear and complete
information
42 The pictures shown do not relate to my
crop
8 User Friendly Device
44 The reference pictures shown are clear
and specific
45 Identification of specimen, pest and
disease is easy because of pictorial
representation
46 Language used in the device is simple and
clear
47 Always an interpreter is needed to
decipher the information
48 The dosages are given in printed formats
so it is easy to follow
9 Agricultural Input Selection
49 Digital extension service helps in
selection of appropriate inputs
50 The information on best management
practices has helped to reduce
indiscriminate use of pesticides and
fertilizers
51 The stepwise procedure is given for input
selection and cultivation practices
52 Many recommended inputs are not
available in regular markets
53 The input suggestions are relevant to my
area
54 The pictures shown helps in right input
selection
10 Market Decision
55 The price forecast helps in taking
decision where to sell the produce
56 We cannot use recommended inputs as
most of them are not available in Raitha
Trang 9Samparka Kendras on subsidy
57 Information about Warehouses is
provided in a comprehensive manner
58 The information on markets help to
decide which crop to grow
59 The demand for a particular crop can be
understood
60 Advisory service includes processing
units and value addition
61 Information on prices in different markets
help in proper decision
11 Follow up support/assistance
62 Advisory services include information on
various schemes
63 TAB provides different formats for
applying to crop insurance schemes
64 It is not of much use because producers
already know about the various schemes
65 Advisory services do not take
responsibility of co-ordination or linkage
66 There is no details in the device about the
various schemes
In conclusion the perception scale developed
was found to be reliable and valid The
perception scale developed was administered
to 40 registered farmers of non sample area,
there were no complications in using the
scale, hence it can be concluded that the scale
developed was useful in explicitly measuring
the perception of farmers towards ICT
enabled farm advisory services Researchers
can use the scale in future for measuring the
perception of farmers in similar studies
References
Dosai, Fahad Owis and Waqar, Muhammed.,
2015, Perception of rural people towards
information and communication
technology (ICT) as influenced by
income levels in district Lodhran –
Pakistan, 14th International Conference,
Paris, 18th Mar., 2015
Edwards AL Techniques of attitude scale construction, Vakils Feffer and Simons Pvt Ltd., Bombay; 1969
Edwards AL Techniques of attitude scale construction Appleton-century crofts, New York; 1957
Ganesh Kumar P, Ratnakar P 2011 A scale to measure farmers‟ attitude towards ICTbased extension services Indian Research Journal of Extension Education Society of Extension Education (SEE), Agra; 2011
Kerlinger FN Foundations of behavioral research Holt, Rinehart and Winston New York; 1973
Likert RA A technique for the measurement
of attitude Arc Psychology; 1932
Thurstone, L L., 1946, Comment American J
Sociol., 52: 39-50
Trang 10How to cite this article:
Rajeshwari, N and Dolli, S S 2020 Development of a Scale to Measure the Perception and Acceptance of Information Technology (IT) Enabled Comprehensive Farm Advisory Services
by Farmers Int.J.Curr.Microbiol.App.Sci 9(07): 3299-3308
doi: https://doi.org/10.20546/ijcmas.2020.907.385